There is an increasing demand for methods and systems capable of detection, quantitative characterization, and notification of the presence of chemical, biological, radiological, nuclear, and/or explosive (“CBRNE”) hazards across a broad range of disciplines, including defense, food safety, homeland security, and medical diagnostics, among many others. For example, rapid screening of unknown liquids and solids on surfaces for low levels of chemical warfare agents (“CWA”), toxic chemicals, narcotics, and explosives in the field is a critical capability need for assuring the safety of warfighters, law enforcement officials, emergency responders, and homeland security officials, among others. Rapid field detection and identification of CBRNE hazards enables an appropriate response and accurate decision making that facilitates time and cost savings as well as proper protective measures. In addition, mitigation of surfaces contaminated with CWAs, some toxic chemicals, and biological toxins is particularly imperative given that lethal doses can occur from dermal exposures of just a few milligrams or less.
While there is existing technology for the detection and identification of chemical and biological hazards on surfaces, these sensors often require a substantial quantity of target analyte to detect and identify the hazard directly on the surface due to interfering background signal from the surface itself. In addition, direct interrogation of chemical and biological materials on the surface may require risk of contamination of the sensor and or personnel. In the case of explosive residues, interrogating of large amounts of target analyte using laser-based spectroscopic methods such as Raman can risk detonation which could injure personnel and/or damage expensive sensors. Therefore, mechanisms to minimize the required amount of target analyte are advantageous to reduce exposures and protect personnel while still providing accurate and rapid characterization. Further, existing surface detection instruments are unable to achieve sufficiently sensitive results in a rapid manner with little or no sample preparation. Analyses requiring sample preparation are time consuming, can be error prone, and may effectively dilute the target analyte resulting in a lower concentration and reduced likelihood of achieving detection. Accordingly, there is a continued need for rapid, accurate, and reliable portable sensor systems capable of being deployed in the field.
One method used for the identification of biological or chemical threats is Raman spectroscopy. Raman is a form of vibrational spectroscopy proven to exhibit excellent selectivity for the purpose of material identification and has been the handheld liquid/solid analyzer of choice for defense and homeland security applications. Raman spectroscopy utilizes a monochromatic laser to interrogate unknown samples. Depending on the specific wavelength of light, the composition of the background material, and properties of the chemical being interrogated, the light can result in absorption, transmission, reflection, or scattering. Light that is scattered from the sample can result in either elastic collisions resulting in Raleigh scattering or inelastic collisions resulting in Raman scattering. Raman light scattering is the result of a photon exciting the molecule through vibration and rotation of its bonds from a ground state to a virtual energy state. Once the molecule relaxes, it emits a photon and returns to a rotational or vibrational state different from the original ground state. The energy delta between these levels results in a shift of the emitted photon's frequency away from the excitation wavelength. The result is a detection method based on the peak intensities at characteristic shifts measured in wavenumber (cm−1) or wavelength (nm) and attributed to specific molecules, thus generating a Raman spectral “fingerprint” by recording the intensity of light as a function of the energy difference between the laser and Raman scattered light. This output is reproducible and allows development of identification algorithms for the spectral fingerprints.
One difficulty with existing Raman detectors is that some background surfaces undergo a competing phenomenon, referred to as fluorescence, which can mask the signal of the target analyte since it is often several orders of magnitude more intense than Raman scattering. For example, highly colored surfaces, plastics, and surfaces with organic binders, paints, and adhesives can obscure a Raman signal and affect the sensitivity of analysis. Modulation of the wavelength of the incident light can alleviate some fluorescence effects, but most fielded instruments operate at a static incident laser wavelength chosen to balance these effects as well as to conserve power, weight, and complexity of the device. The sensor wavelength can be increased to minimize fluorescence but Raman signal diminishes as the 4th power of laser wavelength. Therefore, a Raman sensor at an excitation wavelength of 1064 nm has a signal approximately 3.4 times weaker than a corresponding sensor at a wavelength of 785 nm. Accordingly, for these and other reasons, existing Raman detectors are not sensitive enough to detect low levels of chemical and biological agents. Enabling a surface sampling method, device, and system capable of concentrating the target analyte to maximize the detector signal, while also reducing background interference can consequently dramatically improve sensor sensitivity and selectivity.
Accordingly, there is a continued need for surface sampling methods, devices, and systems to augment the sensitivity of existing detectors in order to provide detection of chemical and/or biological agents in a field-deployed setting in near real-time.